<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
<html xmlns="http://www.w3.org/1999/xhtml">
<head>
<meta http-equiv="Content-Type" content="text/xhtml;charset=UTF-8"/>
<meta http-equiv="X-UA-Compatible" content="IE=9"/>
<meta name="generator" content="Doxygen 1.8.13"/>
<meta name="viewport" content="width=device-width, initial-scale=1"/>
<title>Jetson Inference: segNet Class Reference</title>
<link href="tabs.css" rel="stylesheet" type="text/css"/>
<script type="text/javascript" src="jquery.js"></script>
<script type="text/javascript" src="dynsections.js"></script>
<link href="navtree.css" rel="stylesheet" type="text/css"/>
<script type="text/javascript" src="resize.js"></script>
<script type="text/javascript" src="navtreedata.js"></script>
<script type="text/javascript" src="navtree.js"></script>
<script type="text/javascript">
  $(document).ready(initResizable);
</script>
<link href="search/search.css" rel="stylesheet" type="text/css"/>
<script type="text/javascript" src="search/searchdata.js"></script>
<script type="text/javascript" src="search/search.js"></script>
<link href="doxygen.css" rel="stylesheet" type="text/css" />
</head>
<body>
<div id="top"><!-- do not remove this div, it is closed by doxygen! -->
<div id="titlearea">
<table cellspacing="0" cellpadding="0">
 <tbody>
 <tr style="height: 56px;">
  <td id="projectlogo"><img alt="Logo" src="NVLogo_2D.jpg"/></td>
  <td id="projectalign" style="padding-left: 0.5em;">
   <div id="projectname">Jetson Inference
   </div>
   <div id="projectbrief">DNN Vision Library</div>
  </td>
 </tr>
 </tbody>
</table>
</div>
<!-- end header part -->
<!-- Generated by Doxygen 1.8.13 -->
<script type="text/javascript">
var searchBox = new SearchBox("searchBox", "search",false,'Search');
</script>
<script type="text/javascript" src="menudata.js"></script>
<script type="text/javascript" src="menu.js"></script>
<script type="text/javascript">
$(function() {
  initMenu('',true,false,'search.php','Search');
  $(document).ready(function() { init_search(); });
});
</script>
<div id="main-nav"></div>
</div><!-- top -->
<div id="side-nav" class="ui-resizable side-nav-resizable">
  <div id="nav-tree">
    <div id="nav-tree-contents">
      <div id="nav-sync" class="sync"></div>
    </div>
  </div>
  <div id="splitbar" style="-moz-user-select:none;" 
       class="ui-resizable-handle">
  </div>
</div>
<script type="text/javascript">
$(document).ready(function(){initNavTree('classsegNet.html','');});
</script>
<div id="doc-content">
<!-- window showing the filter options -->
<div id="MSearchSelectWindow"
     onmouseover="return searchBox.OnSearchSelectShow()"
     onmouseout="return searchBox.OnSearchSelectHide()"
     onkeydown="return searchBox.OnSearchSelectKey(event)">
</div>

<!-- iframe showing the search results (closed by default) -->
<div id="MSearchResultsWindow">
<iframe src="javascript:void(0)" frameborder="0" 
        name="MSearchResults" id="MSearchResults">
</iframe>
</div>

<div class="header">
  <div class="summary">
<a href="#pub-types">Public Types</a> &#124;
<a href="#pub-methods">Public Member Functions</a> &#124;
<a href="#pub-static-methods">Static Public Member Functions</a> &#124;
<a href="#pro-methods">Protected Member Functions</a> &#124;
<a href="#pro-attribs">Protected Attributes</a> &#124;
<a href="classsegNet-members.html">List of all members</a>  </div>
  <div class="headertitle">
<div class="title">segNet Class Reference<div class="ingroups"><a class="el" href="group__deepVision.html">DNN Vision Library (jetson-inference)</a> &raquo; <a class="el" href="group__segNet.html">segNet</a></div></div>  </div>
</div><!--header-->
<div class="contents">

<p>Image segmentation with FCN-Alexnet or custom models, using TensorRT.  
 <a href="classsegNet.html#details">More...</a></p>

<p><code>#include &lt;<a class="el" href="segNet_8h_source.html">segNet.h</a>&gt;</code></p>
<div class="dynheader">
Inheritance diagram for segNet:</div>
<div class="dyncontent">
 <div class="center">
  <img src="classsegNet.png" usemap="#segNet_map" alt=""/>
  <map id="segNet_map" name="segNet_map">
<area href="classtensorNet.html" title="Abstract class for loading a tensor network with TensorRT. " alt="tensorNet" shape="rect" coords="0,0,66,24"/>
</map>
 </div></div>
<table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-types"></a>
Public Types</h2></td></tr>
<tr class="memitem:ab561d3c9e3c733e785aaa790f0f2f660"><td class="memItemLeft" align="right" valign="top">enum &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classsegNet.html#ab561d3c9e3c733e785aaa790f0f2f660">NetworkType</a> { <br />
&#160;&#160;<a class="el" href="classsegNet.html#ab561d3c9e3c733e785aaa790f0f2f660adba730fd6f1caee50f8430d96603757a">FCN_ALEXNET_PASCAL_VOC</a>, 
<a class="el" href="classsegNet.html#ab561d3c9e3c733e785aaa790f0f2f660a3cb82f1b884ddc9dc8a51381c2cf8420">FCN_ALEXNET_SYNTHIA_CVPR16</a>, 
<a class="el" href="classsegNet.html#ab561d3c9e3c733e785aaa790f0f2f660a5808394068d715aeff04991dc34b73a8">FCN_ALEXNET_SYNTHIA_SUMMER_HD</a>, 
<a class="el" href="classsegNet.html#ab561d3c9e3c733e785aaa790f0f2f660a245b790d2bc719d2397899bef7472da3">FCN_ALEXNET_SYNTHIA_SUMMER_SD</a>, 
<br />
&#160;&#160;<a class="el" href="classsegNet.html#ab561d3c9e3c733e785aaa790f0f2f660a909c376ffd7d5363aea65c200f2e008e">FCN_ALEXNET_CITYSCAPES_HD</a>, 
<a class="el" href="classsegNet.html#ab561d3c9e3c733e785aaa790f0f2f660a0760a67c5a08aad80d7dc732bc760e31">FCN_ALEXNET_CITYSCAPES_SD</a>, 
<a class="el" href="classsegNet.html#ab561d3c9e3c733e785aaa790f0f2f660a46829d99af463638dfd4e547b0a2a95d">FCN_ALEXNET_AERIAL_FPV_720p</a>, 
<a class="el" href="classsegNet.html#ab561d3c9e3c733e785aaa790f0f2f660a95a81cd526c1ada9d225f6142f5f0f41">SEGNET_CUSTOM</a>
<br />
 }<tr class="memdesc:ab561d3c9e3c733e785aaa790f0f2f660"><td class="mdescLeft">&#160;</td><td class="mdescRight">Enumeration of pretrained/built-in network models.  <a href="classsegNet.html#ab561d3c9e3c733e785aaa790f0f2f660">More...</a><br /></td></tr>
</td></tr>
<tr class="separator:ab561d3c9e3c733e785aaa790f0f2f660"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a5579582306d8b98e3a8acf2b73e13ea0"><td class="memItemLeft" align="right" valign="top">enum &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classsegNet.html#a5579582306d8b98e3a8acf2b73e13ea0">FilterMode</a> { <a class="el" href="classsegNet.html#a5579582306d8b98e3a8acf2b73e13ea0abe4ae38cf99cdab6c3b070ee4a83bb47">FILTER_POINT</a>, 
<a class="el" href="classsegNet.html#a5579582306d8b98e3a8acf2b73e13ea0a034092312a95fa984ab6c8e559c3c9e0">FILTER_LINEAR</a>
 }<tr class="memdesc:a5579582306d8b98e3a8acf2b73e13ea0"><td class="mdescLeft">&#160;</td><td class="mdescRight">Enumeration of mask/overlay filtering modes.  <a href="classsegNet.html#a5579582306d8b98e3a8acf2b73e13ea0">More...</a><br /></td></tr>
</td></tr>
<tr class="separator:a5579582306d8b98e3a8acf2b73e13ea0"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a>
Public Member Functions</h2></td></tr>
<tr class="memitem:a167f9d7e76b2837485278bf7323b4eac"><td class="memItemLeft" align="right" valign="top">virtual&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classsegNet.html#a167f9d7e76b2837485278bf7323b4eac">~segNet</a> ()</td></tr>
<tr class="memdesc:a167f9d7e76b2837485278bf7323b4eac"><td class="mdescLeft">&#160;</td><td class="mdescRight">Destroy.  <a href="#a167f9d7e76b2837485278bf7323b4eac">More...</a><br /></td></tr>
<tr class="separator:a167f9d7e76b2837485278bf7323b4eac"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a2fe1beec3215b5d7744420b57ba397c4"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classsegNet.html#a2fe1beec3215b5d7744420b57ba397c4">Process</a> (float *input, uint32_t width, uint32_t height, const char *ignore_class=&quot;void&quot;)</td></tr>
<tr class="memdesc:a2fe1beec3215b5d7744420b57ba397c4"><td class="mdescLeft">&#160;</td><td class="mdescRight">Perform the initial inferencing processing portion of the segmentation.  <a href="#a2fe1beec3215b5d7744420b57ba397c4">More...</a><br /></td></tr>
<tr class="separator:a2fe1beec3215b5d7744420b57ba397c4"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a1efb45b81c82dd6f74c641ab39a41387"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classsegNet.html#a1efb45b81c82dd6f74c641ab39a41387">Mask</a> (uint8_t *output, uint32_t width, uint32_t height)</td></tr>
<tr class="memdesc:a1efb45b81c82dd6f74c641ab39a41387"><td class="mdescLeft">&#160;</td><td class="mdescRight">Produce a grayscale binary segmentation mask, where the pixel values correspond to the class ID of the corresponding class type.  <a href="#a1efb45b81c82dd6f74c641ab39a41387">More...</a><br /></td></tr>
<tr class="separator:a1efb45b81c82dd6f74c641ab39a41387"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a656d709bbfb00fb0b9b4d55296aae463"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classsegNet.html#a656d709bbfb00fb0b9b4d55296aae463">Mask</a> (float *output, uint32_t width, uint32_t height, <a class="el" href="classsegNet.html#a5579582306d8b98e3a8acf2b73e13ea0">FilterMode</a> filter=<a class="el" href="classsegNet.html#a5579582306d8b98e3a8acf2b73e13ea0a034092312a95fa984ab6c8e559c3c9e0">FILTER_LINEAR</a>)</td></tr>
<tr class="memdesc:a656d709bbfb00fb0b9b4d55296aae463"><td class="mdescLeft">&#160;</td><td class="mdescRight">Produce a colorized RGBA segmentation mask.  <a href="#a656d709bbfb00fb0b9b4d55296aae463">More...</a><br /></td></tr>
<tr class="separator:a656d709bbfb00fb0b9b4d55296aae463"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a3a670c08ad8b13db6ee092c59efe88b8"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classsegNet.html#a3a670c08ad8b13db6ee092c59efe88b8">Overlay</a> (float *output, uint32_t width, uint32_t height, <a class="el" href="classsegNet.html#a5579582306d8b98e3a8acf2b73e13ea0">FilterMode</a> filter=<a class="el" href="classsegNet.html#a5579582306d8b98e3a8acf2b73e13ea0a034092312a95fa984ab6c8e559c3c9e0">FILTER_LINEAR</a>)</td></tr>
<tr class="memdesc:a3a670c08ad8b13db6ee092c59efe88b8"><td class="mdescLeft">&#160;</td><td class="mdescRight">Produce the segmentation overlay alpha blended on top of the original image.  <a href="#a3a670c08ad8b13db6ee092c59efe88b8">More...</a><br /></td></tr>
<tr class="separator:a3a670c08ad8b13db6ee092c59efe88b8"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a04bb46f8a71a45044d324a5e140f0777"><td class="memItemLeft" align="right" valign="top">int&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classsegNet.html#a04bb46f8a71a45044d324a5e140f0777">FindClassID</a> (const char *label_name)</td></tr>
<tr class="memdesc:a04bb46f8a71a45044d324a5e140f0777"><td class="mdescLeft">&#160;</td><td class="mdescRight">Find the ID of a particular class (by label name).  <a href="#a04bb46f8a71a45044d324a5e140f0777">More...</a><br /></td></tr>
<tr class="separator:a04bb46f8a71a45044d324a5e140f0777"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a31e8118b2a38e330b6e087cf6c98396e"><td class="memItemLeft" align="right" valign="top">uint32_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classsegNet.html#a31e8118b2a38e330b6e087cf6c98396e">GetNumClasses</a> () const</td></tr>
<tr class="memdesc:a31e8118b2a38e330b6e087cf6c98396e"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the number of object classes supported in the detector.  <a href="#a31e8118b2a38e330b6e087cf6c98396e">More...</a><br /></td></tr>
<tr class="separator:a31e8118b2a38e330b6e087cf6c98396e"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a895252269f201c23e8887d2774ec5ac4"><td class="memItemLeft" align="right" valign="top">const char *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classsegNet.html#a895252269f201c23e8887d2774ec5ac4">GetClassLabel</a> (uint32_t id) const</td></tr>
<tr class="memdesc:a895252269f201c23e8887d2774ec5ac4"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the description of a particular class.  <a href="#a895252269f201c23e8887d2774ec5ac4">More...</a><br /></td></tr>
<tr class="separator:a895252269f201c23e8887d2774ec5ac4"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a07e9a40b797f22ed0f0e83479be57d17"><td class="memItemLeft" align="right" valign="top">float *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classsegNet.html#a07e9a40b797f22ed0f0e83479be57d17">GetClassColor</a> (uint32_t id) const</td></tr>
<tr class="memdesc:a07e9a40b797f22ed0f0e83479be57d17"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the class synset category of a particular class.  <a href="#a07e9a40b797f22ed0f0e83479be57d17">More...</a><br /></td></tr>
<tr class="separator:a07e9a40b797f22ed0f0e83479be57d17"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a2a9108ad71f4d5f1995ac58282a10b88"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classsegNet.html#a2a9108ad71f4d5f1995ac58282a10b88">SetClassColor</a> (uint32_t classIndex, float r, float g, float b, float a=255.0f)</td></tr>
<tr class="memdesc:a2a9108ad71f4d5f1995ac58282a10b88"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the visualization color of a particular class of object.  <a href="#a2a9108ad71f4d5f1995ac58282a10b88">More...</a><br /></td></tr>
<tr class="separator:a2a9108ad71f4d5f1995ac58282a10b88"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a12d132d630f471c64ad943cbbffb2851"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classsegNet.html#a12d132d630f471c64ad943cbbffb2851">SetGlobalAlpha</a> (float alpha, bool explicit_exempt=true)</td></tr>
<tr class="memdesc:a12d132d630f471c64ad943cbbffb2851"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set a global alpha value for all classes (between 0-255), (optionally except for those that have been explicitly set).  <a href="#a12d132d630f471c64ad943cbbffb2851">More...</a><br /></td></tr>
<tr class="separator:a12d132d630f471c64ad943cbbffb2851"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a973c337a2c3d7371c6b7cebd3aa2ade0"><td class="memItemLeft" align="right" valign="top">const char *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classsegNet.html#a973c337a2c3d7371c6b7cebd3aa2ade0">GetClassPath</a> () const</td></tr>
<tr class="memdesc:a973c337a2c3d7371c6b7cebd3aa2ade0"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the path to the file containing the class label descriptions.  <a href="#a973c337a2c3d7371c6b7cebd3aa2ade0">More...</a><br /></td></tr>
<tr class="separator:a973c337a2c3d7371c6b7cebd3aa2ade0"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a96b6fe6b05534c0792f8cc9353723219"><td class="memItemLeft" align="right" valign="top">uint32_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classsegNet.html#a96b6fe6b05534c0792f8cc9353723219">GetGridWidth</a> () const</td></tr>
<tr class="memdesc:a96b6fe6b05534c0792f8cc9353723219"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the number of columns in the classification grid.  <a href="#a96b6fe6b05534c0792f8cc9353723219">More...</a><br /></td></tr>
<tr class="separator:a96b6fe6b05534c0792f8cc9353723219"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a95980d825a9939d0f48bfb2ef51ebb79"><td class="memItemLeft" align="right" valign="top">uint32_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classsegNet.html#a95980d825a9939d0f48bfb2ef51ebb79">GetGridHeight</a> () const</td></tr>
<tr class="memdesc:a95980d825a9939d0f48bfb2ef51ebb79"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the number of rows in the classification grid.  <a href="#a95980d825a9939d0f48bfb2ef51ebb79">More...</a><br /></td></tr>
<tr class="separator:a95980d825a9939d0f48bfb2ef51ebb79"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a7779565e2e627209d6fc6e7562047431"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classsegNet.html#ab561d3c9e3c733e785aaa790f0f2f660">NetworkType</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classsegNet.html#a7779565e2e627209d6fc6e7562047431">GetNetworkType</a> () const</td></tr>
<tr class="memdesc:a7779565e2e627209d6fc6e7562047431"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the network type (alexnet or googlenet)  <a href="#a7779565e2e627209d6fc6e7562047431">More...</a><br /></td></tr>
<tr class="separator:a7779565e2e627209d6fc6e7562047431"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a94b243146a1391e82612cb70641c4bac"><td class="memItemLeft" align="right" valign="top">const char *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classsegNet.html#a94b243146a1391e82612cb70641c4bac">GetNetworkName</a> () const</td></tr>
<tr class="memdesc:a94b243146a1391e82612cb70641c4bac"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve a string describing the network name.  <a href="#a94b243146a1391e82612cb70641c4bac">More...</a><br /></td></tr>
<tr class="separator:a94b243146a1391e82612cb70641c4bac"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="inherit_header pub_methods_classtensorNet"><td colspan="2" onclick="javascript:toggleInherit('pub_methods_classtensorNet')"><img src="closed.png" alt="-"/>&#160;Public Member Functions inherited from <a class="el" href="classtensorNet.html">tensorNet</a></td></tr>
<tr class="memitem:ad19aafbfa262f9b8ffb0bff561f4d7f7 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">virtual&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ad19aafbfa262f9b8ffb0bff561f4d7f7">~tensorNet</a> ()</td></tr>
<tr class="memdesc:ad19aafbfa262f9b8ffb0bff561f4d7f7 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Destory.  <a href="classtensorNet.html#ad19aafbfa262f9b8ffb0bff561f4d7f7">More...</a><br /></td></tr>
<tr class="separator:ad19aafbfa262f9b8ffb0bff561f4d7f7 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a2e63d4670461814bd863ee0d9bd41526 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a2e63d4670461814bd863ee0d9bd41526">LoadNetwork</a> (const char *prototxt, const char *model, const char *mean=NULL, const char *input_blob=&quot;data&quot;, const char *output_blob=&quot;prob&quot;, uint32_t maxBatchSize=<a class="el" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a>, <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision=<a class="el" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a>, <a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, bool allowGPUFallback=true, nvinfer1::IInt8Calibrator *calibrator=NULL, cudaStream_t stream=NULL)</td></tr>
<tr class="memdesc:a2e63d4670461814bd863ee0d9bd41526 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Load a new network instance.  <a href="classtensorNet.html#a2e63d4670461814bd863ee0d9bd41526">More...</a><br /></td></tr>
<tr class="separator:a2e63d4670461814bd863ee0d9bd41526 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a0a06ffd12b465f39160f4a6925cccd9f inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a0a06ffd12b465f39160f4a6925cccd9f">LoadNetwork</a> (const char *prototxt, const char *model, const char *mean, const char *input_blob, const std::vector&lt; std::string &gt; &amp;output_blobs, uint32_t maxBatchSize=<a class="el" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a>, <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision=<a class="el" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a>, <a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, bool allowGPUFallback=true, nvinfer1::IInt8Calibrator *calibrator=NULL, cudaStream_t stream=NULL)</td></tr>
<tr class="memdesc:a0a06ffd12b465f39160f4a6925cccd9f inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Load a new network instance with multiple output layers.  <a href="classtensorNet.html#a0a06ffd12b465f39160f4a6925cccd9f">More...</a><br /></td></tr>
<tr class="separator:a0a06ffd12b465f39160f4a6925cccd9f inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a168c7f75c9fd6d264afd016e144f3878 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a168c7f75c9fd6d264afd016e144f3878">LoadNetwork</a> (const char *prototxt, const char *model, const char *mean, const char *input_blob, const <a class="el" href="tensorNet_8h.html#a64c8f3dfeacfa962ff9e23c586aedd1b">Dims3</a> &amp;input_dims, const std::vector&lt; std::string &gt; &amp;output_blobs, uint32_t maxBatchSize=<a class="el" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a>, <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision=<a class="el" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a>, <a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, bool allowGPUFallback=true, nvinfer1::IInt8Calibrator *calibrator=NULL, cudaStream_t stream=NULL)</td></tr>
<tr class="memdesc:a168c7f75c9fd6d264afd016e144f3878 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Load a new network instance (this variant is used for UFF models)  <a href="classtensorNet.html#a168c7f75c9fd6d264afd016e144f3878">More...</a><br /></td></tr>
<tr class="separator:a168c7f75c9fd6d264afd016e144f3878 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a3413eb0ad4f240f457f192f39e2e03e8 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a3413eb0ad4f240f457f192f39e2e03e8">EnableLayerProfiler</a> ()</td></tr>
<tr class="memdesc:a3413eb0ad4f240f457f192f39e2e03e8 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Manually enable layer profiling times.  <a href="classtensorNet.html#a3413eb0ad4f240f457f192f39e2e03e8">More...</a><br /></td></tr>
<tr class="separator:a3413eb0ad4f240f457f192f39e2e03e8 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ae49f74ff83e46112a30318fa0576cace inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ae49f74ff83e46112a30318fa0576cace">EnableDebug</a> ()</td></tr>
<tr class="memdesc:ae49f74ff83e46112a30318fa0576cace inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Manually enable debug messages and synchronization.  <a href="classtensorNet.html#ae49f74ff83e46112a30318fa0576cace">More...</a><br /></td></tr>
<tr class="separator:ae49f74ff83e46112a30318fa0576cace inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a7d0ec0d8504ac8b26c5ab4a6136599ca inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a7d0ec0d8504ac8b26c5ab4a6136599ca">AllowGPUFallback</a> () const</td></tr>
<tr class="memdesc:a7d0ec0d8504ac8b26c5ab4a6136599ca inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Return true if GPU fallback is enabled.  <a href="classtensorNet.html#a7d0ec0d8504ac8b26c5ab4a6136599ca">More...</a><br /></td></tr>
<tr class="separator:a7d0ec0d8504ac8b26c5ab4a6136599ca inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a92bb737172d26bda5f67d15346a02514 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top"><a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a92bb737172d26bda5f67d15346a02514">GetDevice</a> () const</td></tr>
<tr class="memdesc:a92bb737172d26bda5f67d15346a02514 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the device being used for execution.  <a href="classtensorNet.html#a92bb737172d26bda5f67d15346a02514">More...</a><br /></td></tr>
<tr class="separator:a92bb737172d26bda5f67d15346a02514 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:afb38b5f171025e987a00214cc4379ca9 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top"><a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#afb38b5f171025e987a00214cc4379ca9">GetPrecision</a> () const</td></tr>
<tr class="memdesc:afb38b5f171025e987a00214cc4379ca9 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the type of precision being used.  <a href="classtensorNet.html#afb38b5f171025e987a00214cc4379ca9">More...</a><br /></td></tr>
<tr class="separator:afb38b5f171025e987a00214cc4379ca9 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a6b8e8dba05bc5c677027913d8c64f259 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a6b8e8dba05bc5c677027913d8c64f259">IsPrecision</a> (<a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> type) const</td></tr>
<tr class="memdesc:a6b8e8dba05bc5c677027913d8c64f259 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Check if a particular precision is being used.  <a href="classtensorNet.html#a6b8e8dba05bc5c677027913d8c64f259">More...</a><br /></td></tr>
<tr class="separator:a6b8e8dba05bc5c677027913d8c64f259 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a34e350ec6185277ac09ae55a79403e62 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">cudaStream_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a34e350ec6185277ac09ae55a79403e62">GetStream</a> () const</td></tr>
<tr class="memdesc:a34e350ec6185277ac09ae55a79403e62 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the stream that the device is operating on.  <a href="classtensorNet.html#a34e350ec6185277ac09ae55a79403e62">More...</a><br /></td></tr>
<tr class="separator:a34e350ec6185277ac09ae55a79403e62 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a78cecfb7505be0ea59d29041abc85cbb inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">cudaStream_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a78cecfb7505be0ea59d29041abc85cbb">CreateStream</a> (bool nonBlocking=true)</td></tr>
<tr class="memdesc:a78cecfb7505be0ea59d29041abc85cbb inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Create and use a new stream for execution.  <a href="classtensorNet.html#a78cecfb7505be0ea59d29041abc85cbb">More...</a><br /></td></tr>
<tr class="separator:a78cecfb7505be0ea59d29041abc85cbb inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a679b177784c85bfdba63dcd1008ff633 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a679b177784c85bfdba63dcd1008ff633">SetStream</a> (cudaStream_t stream)</td></tr>
<tr class="memdesc:a679b177784c85bfdba63dcd1008ff633 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the stream that the device is operating on.  <a href="classtensorNet.html#a679b177784c85bfdba63dcd1008ff633">More...</a><br /></td></tr>
<tr class="separator:a679b177784c85bfdba63dcd1008ff633 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a624881afe27acd2b2fff0f0f75308ea2 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">const char *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a624881afe27acd2b2fff0f0f75308ea2">GetPrototxtPath</a> () const</td></tr>
<tr class="memdesc:a624881afe27acd2b2fff0f0f75308ea2 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the path to the network prototxt file.  <a href="classtensorNet.html#a624881afe27acd2b2fff0f0f75308ea2">More...</a><br /></td></tr>
<tr class="separator:a624881afe27acd2b2fff0f0f75308ea2 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ac74d7f0571b7782b945ff85fd6894044 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">const char *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ac74d7f0571b7782b945ff85fd6894044">GetModelPath</a> () const</td></tr>
<tr class="memdesc:ac74d7f0571b7782b945ff85fd6894044 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the path to the network model file.  <a href="classtensorNet.html#ac74d7f0571b7782b945ff85fd6894044">More...</a><br /></td></tr>
<tr class="separator:ac74d7f0571b7782b945ff85fd6894044 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:acfa7f1f01b46f658ffc96f8a002e8d48 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top"><a class="el" href="group__tensorNet.html#ga5d4597e0e7beae7133d542e220528725">modelType</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#acfa7f1f01b46f658ffc96f8a002e8d48">GetModelType</a> () const</td></tr>
<tr class="memdesc:acfa7f1f01b46f658ffc96f8a002e8d48 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the format of the network model.  <a href="classtensorNet.html#acfa7f1f01b46f658ffc96f8a002e8d48">More...</a><br /></td></tr>
<tr class="separator:acfa7f1f01b46f658ffc96f8a002e8d48 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a0a09d691ea080bd9734c5782c8fff6fd inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a0a09d691ea080bd9734c5782c8fff6fd">IsModelType</a> (<a class="el" href="group__tensorNet.html#ga5d4597e0e7beae7133d542e220528725">modelType</a> type) const</td></tr>
<tr class="memdesc:a0a09d691ea080bd9734c5782c8fff6fd inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Return true if the model is of the specified format.  <a href="classtensorNet.html#a0a09d691ea080bd9734c5782c8fff6fd">More...</a><br /></td></tr>
<tr class="separator:a0a09d691ea080bd9734c5782c8fff6fd inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a49faef5920860345e503023b7c84423c inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">float&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a49faef5920860345e503023b7c84423c">GetNetworkTime</a> ()</td></tr>
<tr class="memdesc:a49faef5920860345e503023b7c84423c inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the network runtime (in milliseconds).  <a href="classtensorNet.html#a49faef5920860345e503023b7c84423c">More...</a><br /></td></tr>
<tr class="separator:a49faef5920860345e503023b7c84423c inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ad266f93035a80dca80cd84d971e4f69b inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">float2&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ad266f93035a80dca80cd84d971e4f69b">GetProfilerTime</a> (<a class="el" href="group__tensorNet.html#gae34d45c0faa674ef4cc0fbfc8fae5809">profilerQuery</a> query)</td></tr>
<tr class="memdesc:ad266f93035a80dca80cd84d971e4f69b inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the profiler runtime (in milliseconds).  <a href="classtensorNet.html#ad266f93035a80dca80cd84d971e4f69b">More...</a><br /></td></tr>
<tr class="separator:ad266f93035a80dca80cd84d971e4f69b inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a27cf81b3fecf93d2e63a61220a54b393 inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">float&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a27cf81b3fecf93d2e63a61220a54b393">GetProfilerTime</a> (<a class="el" href="group__tensorNet.html#gae34d45c0faa674ef4cc0fbfc8fae5809">profilerQuery</a> query, <a class="el" href="group__tensorNet.html#gaaa4127ed22c7165a32d0474ebf97975e">profilerDevice</a> device)</td></tr>
<tr class="memdesc:a27cf81b3fecf93d2e63a61220a54b393 inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the profiler runtime (in milliseconds).  <a href="classtensorNet.html#a27cf81b3fecf93d2e63a61220a54b393">More...</a><br /></td></tr>
<tr class="separator:a27cf81b3fecf93d2e63a61220a54b393 inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:afc0f50abcf6ac71e96d51eba3ed53d4b inherit pub_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#afc0f50abcf6ac71e96d51eba3ed53d4b">PrintProfilerTimes</a> ()</td></tr>
<tr class="memdesc:afc0f50abcf6ac71e96d51eba3ed53d4b inherit pub_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Print the profiler times (in millseconds).  <a href="classtensorNet.html#afc0f50abcf6ac71e96d51eba3ed53d4b">More...</a><br /></td></tr>
<tr class="separator:afc0f50abcf6ac71e96d51eba3ed53d4b inherit pub_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-static-methods"></a>
Static Public Member Functions</h2></td></tr>
<tr class="memitem:a586492c234d2dc924458e99d6026dbb4"><td class="memItemLeft" align="right" valign="top">static <a class="el" href="classsegNet.html#ab561d3c9e3c733e785aaa790f0f2f660">NetworkType</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classsegNet.html#a586492c234d2dc924458e99d6026dbb4">NetworkTypeFromStr</a> (const char *model_name)</td></tr>
<tr class="memdesc:a586492c234d2dc924458e99d6026dbb4"><td class="mdescLeft">&#160;</td><td class="mdescRight">Parse a string from one of the built-in pretrained models.  <a href="#a586492c234d2dc924458e99d6026dbb4">More...</a><br /></td></tr>
<tr class="separator:a586492c234d2dc924458e99d6026dbb4"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a299e7f53cde4e3e25cd00829dc181a10"><td class="memItemLeft" align="right" valign="top">static <a class="el" href="classsegNet.html#a5579582306d8b98e3a8acf2b73e13ea0">FilterMode</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classsegNet.html#a299e7f53cde4e3e25cd00829dc181a10">FilterModeFromStr</a> (const char *str, <a class="el" href="classsegNet.html#a5579582306d8b98e3a8acf2b73e13ea0">FilterMode</a> default_value=<a class="el" href="classsegNet.html#a5579582306d8b98e3a8acf2b73e13ea0a034092312a95fa984ab6c8e559c3c9e0">FILTER_LINEAR</a>)</td></tr>
<tr class="memdesc:a299e7f53cde4e3e25cd00829dc181a10"><td class="mdescLeft">&#160;</td><td class="mdescRight">Parse a string from one of the FilterMode values.  <a href="#a299e7f53cde4e3e25cd00829dc181a10">More...</a><br /></td></tr>
<tr class="separator:a299e7f53cde4e3e25cd00829dc181a10"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a0679f72dbced85d919d01af841c67db9"><td class="memItemLeft" align="right" valign="top">static <a class="el" href="classsegNet.html">segNet</a> *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classsegNet.html#a0679f72dbced85d919d01af841c67db9">Create</a> (<a class="el" href="classsegNet.html#ab561d3c9e3c733e785aaa790f0f2f660">NetworkType</a> networkType=<a class="el" href="classsegNet.html#ab561d3c9e3c733e785aaa790f0f2f660a0760a67c5a08aad80d7dc732bc760e31">FCN_ALEXNET_CITYSCAPES_SD</a>, uint32_t maxBatchSize=<a class="el" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a>, <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision=<a class="el" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a>, <a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, bool allowGPUFallback=true)</td></tr>
<tr class="memdesc:a0679f72dbced85d919d01af841c67db9"><td class="mdescLeft">&#160;</td><td class="mdescRight">Load a new network instance.  <a href="#a0679f72dbced85d919d01af841c67db9">More...</a><br /></td></tr>
<tr class="separator:a0679f72dbced85d919d01af841c67db9"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aee471c7f0b830babb826648db2692edb"><td class="memItemLeft" align="right" valign="top">static <a class="el" href="classsegNet.html">segNet</a> *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classsegNet.html#aee471c7f0b830babb826648db2692edb">Create</a> (const char *prototxt_path, const char *model_path, const char *class_labels, const char *class_colors=NULL, const char *input=<a class="el" href="group__segNet.html#ga33b5fd20f8ed468725c55eb0bcc5af71">SEGNET_DEFAULT_INPUT</a>, const char *output=<a class="el" href="group__segNet.html#ga05c359c7dcd0c1e855543a3a9a18c422">SEGNET_DEFAULT_OUTPUT</a>, uint32_t maxBatchSize=<a class="el" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a>, <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision=<a class="el" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a>, <a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, bool allowGPUFallback=true)</td></tr>
<tr class="memdesc:aee471c7f0b830babb826648db2692edb"><td class="mdescLeft">&#160;</td><td class="mdescRight">Load a new network instance.  <a href="#aee471c7f0b830babb826648db2692edb">More...</a><br /></td></tr>
<tr class="separator:aee471c7f0b830babb826648db2692edb"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aa4186752e1402963fdde8e2d6f2613d7"><td class="memItemLeft" align="right" valign="top">static <a class="el" href="classsegNet.html">segNet</a> *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classsegNet.html#aa4186752e1402963fdde8e2d6f2613d7">Create</a> (int argc, char **argv)</td></tr>
<tr class="memdesc:aa4186752e1402963fdde8e2d6f2613d7"><td class="mdescLeft">&#160;</td><td class="mdescRight">Load a new network instance by parsing the command line.  <a href="#aa4186752e1402963fdde8e2d6f2613d7">More...</a><br /></td></tr>
<tr class="separator:aa4186752e1402963fdde8e2d6f2613d7"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="inherit_header pub_static_methods_classtensorNet"><td colspan="2" onclick="javascript:toggleInherit('pub_static_methods_classtensorNet')"><img src="closed.png" alt="-"/>&#160;Static Public Member Functions inherited from <a class="el" href="classtensorNet.html">tensorNet</a></td></tr>
<tr class="memitem:abe33fae5332296e2d917cb4ce435e255 inherit pub_static_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">static <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#abe33fae5332296e2d917cb4ce435e255">FindFastestPrecision</a> (<a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, bool allowInt8=true)</td></tr>
<tr class="memdesc:abe33fae5332296e2d917cb4ce435e255 inherit pub_static_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Determine the fastest native precision on a device.  <a href="classtensorNet.html#abe33fae5332296e2d917cb4ce435e255">More...</a><br /></td></tr>
<tr class="separator:abe33fae5332296e2d917cb4ce435e255 inherit pub_static_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ae88436e652afdd7bceef7cb7c5fde7a6 inherit pub_static_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">static std::vector&lt; <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ae88436e652afdd7bceef7cb7c5fde7a6">DetectNativePrecisions</a> (<a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>)</td></tr>
<tr class="memdesc:ae88436e652afdd7bceef7cb7c5fde7a6 inherit pub_static_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Detect the precisions supported natively on a device.  <a href="classtensorNet.html#ae88436e652afdd7bceef7cb7c5fde7a6">More...</a><br /></td></tr>
<tr class="separator:ae88436e652afdd7bceef7cb7c5fde7a6 inherit pub_static_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aa3bf1a3bf1fca38b39a200b4d8f727b2 inherit pub_static_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">static bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#aa3bf1a3bf1fca38b39a200b4d8f727b2">DetectNativePrecision</a> (const std::vector&lt; <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> &gt; &amp;nativeTypes, <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> type)</td></tr>
<tr class="memdesc:aa3bf1a3bf1fca38b39a200b4d8f727b2 inherit pub_static_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Detect if a particular precision is supported natively.  <a href="classtensorNet.html#aa3bf1a3bf1fca38b39a200b4d8f727b2">More...</a><br /></td></tr>
<tr class="separator:aa3bf1a3bf1fca38b39a200b4d8f727b2 inherit pub_static_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a7d72ec8bbaf61278ce533afd60d5391c inherit pub_static_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">static bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a7d72ec8bbaf61278ce533afd60d5391c">DetectNativePrecision</a> (<a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision, <a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>)</td></tr>
<tr class="memdesc:a7d72ec8bbaf61278ce533afd60d5391c inherit pub_static_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Detect if a particular precision is supported natively.  <a href="classtensorNet.html#a7d72ec8bbaf61278ce533afd60d5391c">More...</a><br /></td></tr>
<tr class="separator:a7d72ec8bbaf61278ce533afd60d5391c inherit pub_static_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pro-methods"></a>
Protected Member Functions</h2></td></tr>
<tr class="memitem:af2a45b6307104ed74714349becc0495c"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classsegNet.html#af2a45b6307104ed74714349becc0495c">segNet</a> ()</td></tr>
<tr class="separator:af2a45b6307104ed74714349becc0495c"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a3b98b9827d5c07e84ed6711414b96554"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classsegNet.html#a3b98b9827d5c07e84ed6711414b96554">classify</a> (const char *ignore_class)</td></tr>
<tr class="separator:a3b98b9827d5c07e84ed6711414b96554"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a3691c49b64e20993bb2440129a7cd81e"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classsegNet.html#a3691c49b64e20993bb2440129a7cd81e">overlayPoint</a> (float *input, uint32_t in_width, uint32_t in_height, float *output, uint32_t out_width, uint32_t out_height, bool mask_only)</td></tr>
<tr class="separator:a3691c49b64e20993bb2440129a7cd81e"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a1365e866302f49f6fe7f9fe95cbe6a72"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classsegNet.html#a1365e866302f49f6fe7f9fe95cbe6a72">overlayLinear</a> (float *input, uint32_t in_width, uint32_t in_height, float *output, uint32_t out_width, uint32_t out_height, bool mask_only)</td></tr>
<tr class="separator:a1365e866302f49f6fe7f9fe95cbe6a72"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a218a2c71cb4d59476070385c7370f789"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classsegNet.html#a218a2c71cb4d59476070385c7370f789">loadClassColors</a> (const char *filename)</td></tr>
<tr class="separator:a218a2c71cb4d59476070385c7370f789"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a31d2bd6ddf05ce178a8e6c5b88247075"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classsegNet.html#a31d2bd6ddf05ce178a8e6c5b88247075">loadClassLabels</a> (const char *filename)</td></tr>
<tr class="separator:a31d2bd6ddf05ce178a8e6c5b88247075"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="inherit_header pro_methods_classtensorNet"><td colspan="2" onclick="javascript:toggleInherit('pro_methods_classtensorNet')"><img src="closed.png" alt="-"/>&#160;Protected Member Functions inherited from <a class="el" href="classtensorNet.html">tensorNet</a></td></tr>
<tr class="memitem:ab6e617d96e5542bef023ee9d4c96388a inherit pro_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ab6e617d96e5542bef023ee9d4c96388a">tensorNet</a> ()</td></tr>
<tr class="memdesc:ab6e617d96e5542bef023ee9d4c96388a inherit pro_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Constructor.  <a href="classtensorNet.html#ab6e617d96e5542bef023ee9d4c96388a">More...</a><br /></td></tr>
<tr class="separator:ab6e617d96e5542bef023ee9d4c96388a inherit pro_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a081b95210634e8ddb21e99d9ad1aa497 inherit pro_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a081b95210634e8ddb21e99d9ad1aa497">ProfileModel</a> (const std::string &amp;deployFile, const std::string &amp;modelFile, const char *input, const <a class="el" href="tensorNet_8h.html#a64c8f3dfeacfa962ff9e23c586aedd1b">Dims3</a> &amp;inputDims, const std::vector&lt; std::string &gt; &amp;outputs, uint32_t maxBatchSize, <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision, <a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device, bool allowGPUFallback, nvinfer1::IInt8Calibrator *calibrator, std::ostream &amp;modelStream)</td></tr>
<tr class="memdesc:a081b95210634e8ddb21e99d9ad1aa497 inherit pro_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Create and output an optimized network model.  <a href="classtensorNet.html#a081b95210634e8ddb21e99d9ad1aa497">More...</a><br /></td></tr>
<tr class="separator:a081b95210634e8ddb21e99d9ad1aa497 inherit pro_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a088c3bf591e45e52ec227491f6f299ad inherit pro_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a088c3bf591e45e52ec227491f6f299ad">PROFILER_BEGIN</a> (<a class="el" href="group__tensorNet.html#gae34d45c0faa674ef4cc0fbfc8fae5809">profilerQuery</a> query)</td></tr>
<tr class="memdesc:a088c3bf591e45e52ec227491f6f299ad inherit pro_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Begin a profiling query, before network is run.  <a href="classtensorNet.html#a088c3bf591e45e52ec227491f6f299ad">More...</a><br /></td></tr>
<tr class="separator:a088c3bf591e45e52ec227491f6f299ad inherit pro_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ac8582b9a6099e3265da4c3f9fdf804ea inherit pro_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ac8582b9a6099e3265da4c3f9fdf804ea">PROFILER_END</a> (<a class="el" href="group__tensorNet.html#gae34d45c0faa674ef4cc0fbfc8fae5809">profilerQuery</a> query)</td></tr>
<tr class="memdesc:ac8582b9a6099e3265da4c3f9fdf804ea inherit pro_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">End a profiling query, after the network is run.  <a href="classtensorNet.html#ac8582b9a6099e3265da4c3f9fdf804ea">More...</a><br /></td></tr>
<tr class="separator:ac8582b9a6099e3265da4c3f9fdf804ea inherit pro_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ae2e0ae17baf6e1975aaad7a7f5c60ce9 inherit pro_methods_classtensorNet"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ae2e0ae17baf6e1975aaad7a7f5c60ce9">PROFILER_QUERY</a> (<a class="el" href="group__tensorNet.html#gae34d45c0faa674ef4cc0fbfc8fae5809">profilerQuery</a> query)</td></tr>
<tr class="memdesc:ae2e0ae17baf6e1975aaad7a7f5c60ce9 inherit pro_methods_classtensorNet"><td class="mdescLeft">&#160;</td><td class="mdescRight">Query the CUDA part of a profiler query.  <a href="classtensorNet.html#ae2e0ae17baf6e1975aaad7a7f5c60ce9">More...</a><br /></td></tr>
<tr class="separator:ae2e0ae17baf6e1975aaad7a7f5c60ce9 inherit pro_methods_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pro-attribs"></a>
Protected Attributes</h2></td></tr>
<tr class="memitem:a5763fca156e99d9fe07dcbf626489b0e"><td class="memItemLeft" align="right" valign="top">std::vector&lt; std::string &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classsegNet.html#a5763fca156e99d9fe07dcbf626489b0e">mClassLabels</a></td></tr>
<tr class="separator:a5763fca156e99d9fe07dcbf626489b0e"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:af9a9bd73dc17940aa87aacba2001b09b"><td class="memItemLeft" align="right" valign="top">std::string&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classsegNet.html#af9a9bd73dc17940aa87aacba2001b09b">mClassPath</a></td></tr>
<tr class="separator:af9a9bd73dc17940aa87aacba2001b09b"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:adbf7de9cddd287f99a1ef7edf531325c"><td class="memItemLeft" align="right" valign="top">float *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classsegNet.html#adbf7de9cddd287f99a1ef7edf531325c">mClassColors</a> [2]</td></tr>
<tr class="memdesc:adbf7de9cddd287f99a1ef7edf531325c"><td class="mdescLeft">&#160;</td><td class="mdescRight">array of overlay colors in shared CPU/GPU memory  <a href="#adbf7de9cddd287f99a1ef7edf531325c">More...</a><br /></td></tr>
<tr class="separator:adbf7de9cddd287f99a1ef7edf531325c"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ac1f23154131a719769edf4811f8762ef"><td class="memItemLeft" align="right" valign="top">uint8_t *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classsegNet.html#ac1f23154131a719769edf4811f8762ef">mClassMap</a> [2]</td></tr>
<tr class="memdesc:ac1f23154131a719769edf4811f8762ef"><td class="mdescLeft">&#160;</td><td class="mdescRight">runtime buffer for the argmax-classified class index of each tile  <a href="#ac1f23154131a719769edf4811f8762ef">More...</a><br /></td></tr>
<tr class="separator:ac1f23154131a719769edf4811f8762ef"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ad7970fe3c387258828d628bd5f08e57a"><td class="memItemLeft" align="right" valign="top">float *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classsegNet.html#ad7970fe3c387258828d628bd5f08e57a">mLastInputImg</a></td></tr>
<tr class="memdesc:ad7970fe3c387258828d628bd5f08e57a"><td class="mdescLeft">&#160;</td><td class="mdescRight">last input image to be processed, stored for overlay  <a href="#ad7970fe3c387258828d628bd5f08e57a">More...</a><br /></td></tr>
<tr class="separator:ad7970fe3c387258828d628bd5f08e57a"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ad984bfe4460621a78440bfb4768f4e8e"><td class="memItemLeft" align="right" valign="top">uint32_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classsegNet.html#ad984bfe4460621a78440bfb4768f4e8e">mLastInputWidth</a></td></tr>
<tr class="memdesc:ad984bfe4460621a78440bfb4768f4e8e"><td class="mdescLeft">&#160;</td><td class="mdescRight">width in pixels of last input image to be processed  <a href="#ad984bfe4460621a78440bfb4768f4e8e">More...</a><br /></td></tr>
<tr class="separator:ad984bfe4460621a78440bfb4768f4e8e"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a4341b8ae226236eef40867bab4c7f251"><td class="memItemLeft" align="right" valign="top">uint32_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classsegNet.html#a4341b8ae226236eef40867bab4c7f251">mLastInputHeight</a></td></tr>
<tr class="memdesc:a4341b8ae226236eef40867bab4c7f251"><td class="mdescLeft">&#160;</td><td class="mdescRight">height in pixels of last input image to be processed  <a href="#a4341b8ae226236eef40867bab4c7f251">More...</a><br /></td></tr>
<tr class="separator:a4341b8ae226236eef40867bab4c7f251"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a9719a3525dd0ee4bcc0e954187dc7323"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classsegNet.html#ab561d3c9e3c733e785aaa790f0f2f660">NetworkType</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classsegNet.html#a9719a3525dd0ee4bcc0e954187dc7323">mNetworkType</a></td></tr>
<tr class="memdesc:a9719a3525dd0ee4bcc0e954187dc7323"><td class="mdescLeft">&#160;</td><td class="mdescRight">Pretrained built-in model type enumeration.  <a href="#a9719a3525dd0ee4bcc0e954187dc7323">More...</a><br /></td></tr>
<tr class="separator:a9719a3525dd0ee4bcc0e954187dc7323"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="inherit_header pro_attribs_classtensorNet"><td colspan="2" onclick="javascript:toggleInherit('pro_attribs_classtensorNet')"><img src="closed.png" alt="-"/>&#160;Protected Attributes inherited from <a class="el" href="classtensorNet.html">tensorNet</a></td></tr>
<tr class="memitem:a6bd429ccb1dc3717b2a4a5ad8e555cd0 inherit pro_attribs_classtensorNet"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classtensorNet_1_1Logger.html">tensorNet::Logger</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a6bd429ccb1dc3717b2a4a5ad8e555cd0">gLogger</a></td></tr>
<tr class="separator:a6bd429ccb1dc3717b2a4a5ad8e555cd0 inherit pro_attribs_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ae1f74819d644d0f289253fbcf5d0655f inherit pro_attribs_classtensorNet"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classtensorNet_1_1Profiler.html">tensorNet::Profiler</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ae1f74819d644d0f289253fbcf5d0655f">gProfiler</a></td></tr>
<tr class="separator:ae1f74819d644d0f289253fbcf5d0655f inherit pro_attribs_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a54005b86b851fa71aeb7a83d4ad32362 inherit pro_attribs_classtensorNet"><td class="memItemLeft" align="right" valign="top">std::string&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a54005b86b851fa71aeb7a83d4ad32362">mPrototxtPath</a></td></tr>
<tr class="separator:a54005b86b851fa71aeb7a83d4ad32362 inherit pro_attribs_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a7cb91e06b296431680d20e7e9fb0187d inherit pro_attribs_classtensorNet"><td class="memItemLeft" align="right" valign="top">std::string&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a7cb91e06b296431680d20e7e9fb0187d">mModelPath</a></td></tr>
<tr class="separator:a7cb91e06b296431680d20e7e9fb0187d inherit pro_attribs_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a11eeaa1e454a97a5634c7fb5ea1bc23d inherit pro_attribs_classtensorNet"><td class="memItemLeft" align="right" valign="top">std::string&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a11eeaa1e454a97a5634c7fb5ea1bc23d">mMeanPath</a></td></tr>
<tr class="separator:a11eeaa1e454a97a5634c7fb5ea1bc23d inherit pro_attribs_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ac040cf851463cd595a20a9400a5833c2 inherit pro_attribs_classtensorNet"><td class="memItemLeft" align="right" valign="top">std::string&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ac040cf851463cd595a20a9400a5833c2">mInputBlobName</a></td></tr>
<tr class="separator:ac040cf851463cd595a20a9400a5833c2 inherit pro_attribs_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aaa9ac0fae88a426f1a5325886da3b009 inherit pro_attribs_classtensorNet"><td class="memItemLeft" align="right" valign="top">std::string&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#aaa9ac0fae88a426f1a5325886da3b009">mCacheEnginePath</a></td></tr>
<tr class="separator:aaa9ac0fae88a426f1a5325886da3b009 inherit pro_attribs_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a64fccb1894b0926e54a18fa47a271c70 inherit pro_attribs_classtensorNet"><td class="memItemLeft" align="right" valign="top">std::string&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a64fccb1894b0926e54a18fa47a271c70">mCacheCalibrationPath</a></td></tr>
<tr class="separator:a64fccb1894b0926e54a18fa47a271c70 inherit pro_attribs_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a2f14a2f4a4dfbb51b80f80a2e47a695c inherit pro_attribs_classtensorNet"><td class="memItemLeft" align="right" valign="top"><a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a2f14a2f4a4dfbb51b80f80a2e47a695c">mDevice</a></td></tr>
<tr class="separator:a2f14a2f4a4dfbb51b80f80a2e47a695c inherit pro_attribs_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a164c1dcf9dcbc085c1b421855eda665f inherit pro_attribs_classtensorNet"><td class="memItemLeft" align="right" valign="top"><a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a164c1dcf9dcbc085c1b421855eda665f">mPrecision</a></td></tr>
<tr class="separator:a164c1dcf9dcbc085c1b421855eda665f inherit pro_attribs_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ab5c88cf4590b53804ebedaa292d1402c inherit pro_attribs_classtensorNet"><td class="memItemLeft" align="right" valign="top"><a class="el" href="group__tensorNet.html#ga5d4597e0e7beae7133d542e220528725">modelType</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ab5c88cf4590b53804ebedaa292d1402c">mModelType</a></td></tr>
<tr class="separator:ab5c88cf4590b53804ebedaa292d1402c inherit pro_attribs_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a1ed6e418a135650c7cf91498379727ae inherit pro_attribs_classtensorNet"><td class="memItemLeft" align="right" valign="top">cudaStream_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a1ed6e418a135650c7cf91498379727ae">mStream</a></td></tr>
<tr class="separator:a1ed6e418a135650c7cf91498379727ae inherit pro_attribs_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aac52fdcc0579c0426e21141636349dea inherit pro_attribs_classtensorNet"><td class="memItemLeft" align="right" valign="top">cudaEvent_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#aac52fdcc0579c0426e21141636349dea">mEventsGPU</a> [<a class="el" href="group__tensorNet.html#ggae34d45c0faa674ef4cc0fbfc8fae5809af9132edd0371e716aed4d46e3da5e9ea">PROFILER_TOTAL</a> *2]</td></tr>
<tr class="separator:aac52fdcc0579c0426e21141636349dea inherit pro_attribs_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:af4cb4b37a74806164257e9529cb8ed70 inherit pro_attribs_classtensorNet"><td class="memItemLeft" align="right" valign="top">timespec&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#af4cb4b37a74806164257e9529cb8ed70">mEventsCPU</a> [<a class="el" href="group__tensorNet.html#ggae34d45c0faa674ef4cc0fbfc8fae5809af9132edd0371e716aed4d46e3da5e9ea">PROFILER_TOTAL</a> *2]</td></tr>
<tr class="separator:af4cb4b37a74806164257e9529cb8ed70 inherit pro_attribs_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a275ce2318a63dcaafc1e0120a53fe606 inherit pro_attribs_classtensorNet"><td class="memItemLeft" align="right" valign="top">nvinfer1::IRuntime *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a275ce2318a63dcaafc1e0120a53fe606">mInfer</a></td></tr>
<tr class="separator:a275ce2318a63dcaafc1e0120a53fe606 inherit pro_attribs_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ad6d2272a2560bec119fa570438e3eb19 inherit pro_attribs_classtensorNet"><td class="memItemLeft" align="right" valign="top">nvinfer1::ICudaEngine *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ad6d2272a2560bec119fa570438e3eb19">mEngine</a></td></tr>
<tr class="separator:ad6d2272a2560bec119fa570438e3eb19 inherit pro_attribs_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a2c745474e60145ee826b53e294e7f478 inherit pro_attribs_classtensorNet"><td class="memItemLeft" align="right" valign="top">nvinfer1::IExecutionContext *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a2c745474e60145ee826b53e294e7f478">mContext</a></td></tr>
<tr class="separator:a2c745474e60145ee826b53e294e7f478 inherit pro_attribs_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:accab52fa354232149048440da0071573 inherit pro_attribs_classtensorNet"><td class="memItemLeft" align="right" valign="top">uint32_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#accab52fa354232149048440da0071573">mWidth</a></td></tr>
<tr class="separator:accab52fa354232149048440da0071573 inherit pro_attribs_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:abc0c2b349cb27ddf6e42f668fa582a34 inherit pro_attribs_classtensorNet"><td class="memItemLeft" align="right" valign="top">uint32_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#abc0c2b349cb27ddf6e42f668fa582a34">mHeight</a></td></tr>
<tr class="separator:abc0c2b349cb27ddf6e42f668fa582a34 inherit pro_attribs_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ac4e059779c0fba12c1ec2380c05b8104 inherit pro_attribs_classtensorNet"><td class="memItemLeft" align="right" valign="top">uint32_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ac4e059779c0fba12c1ec2380c05b8104">mInputSize</a></td></tr>
<tr class="separator:ac4e059779c0fba12c1ec2380c05b8104 inherit pro_attribs_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a03d8f99ffd7dfdc4bab679592e97c4f2 inherit pro_attribs_classtensorNet"><td class="memItemLeft" align="right" valign="top">float *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a03d8f99ffd7dfdc4bab679592e97c4f2">mInputCPU</a></td></tr>
<tr class="separator:a03d8f99ffd7dfdc4bab679592e97c4f2 inherit pro_attribs_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a9530becbabaf219e3e85d0df5f4cc2b6 inherit pro_attribs_classtensorNet"><td class="memItemLeft" align="right" valign="top">float *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a9530becbabaf219e3e85d0df5f4cc2b6">mInputCUDA</a></td></tr>
<tr class="separator:a9530becbabaf219e3e85d0df5f4cc2b6 inherit pro_attribs_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a32dbfb5b3d2cb82002ec288c237a0c9c inherit pro_attribs_classtensorNet"><td class="memItemLeft" align="right" valign="top">float2&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a32dbfb5b3d2cb82002ec288c237a0c9c">mProfilerTimes</a> [<a class="el" href="group__tensorNet.html#ggae34d45c0faa674ef4cc0fbfc8fae5809af9132edd0371e716aed4d46e3da5e9ea">PROFILER_TOTAL</a>+1]</td></tr>
<tr class="separator:a32dbfb5b3d2cb82002ec288c237a0c9c inherit pro_attribs_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a545348243b65ce04047fd10d47e1716c inherit pro_attribs_classtensorNet"><td class="memItemLeft" align="right" valign="top">uint32_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a545348243b65ce04047fd10d47e1716c">mProfilerQueriesUsed</a></td></tr>
<tr class="separator:a545348243b65ce04047fd10d47e1716c inherit pro_attribs_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a3b5be95254ce71931305f4086f23f18a inherit pro_attribs_classtensorNet"><td class="memItemLeft" align="right" valign="top">uint32_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a3b5be95254ce71931305f4086f23f18a">mProfilerQueriesDone</a></td></tr>
<tr class="separator:a3b5be95254ce71931305f4086f23f18a inherit pro_attribs_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a0027d8b3617cfc905465925dd6d84b0f inherit pro_attribs_classtensorNet"><td class="memItemLeft" align="right" valign="top">uint32_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a0027d8b3617cfc905465925dd6d84b0f">mMaxBatchSize</a></td></tr>
<tr class="separator:a0027d8b3617cfc905465925dd6d84b0f inherit pro_attribs_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aa8bbf97d979c62018f42cc44b5cb81e8 inherit pro_attribs_classtensorNet"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#aa8bbf97d979c62018f42cc44b5cb81e8">mEnableProfiler</a></td></tr>
<tr class="separator:aa8bbf97d979c62018f42cc44b5cb81e8 inherit pro_attribs_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a84ad901a2a0dc4aaf740d40307437b2b inherit pro_attribs_classtensorNet"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a84ad901a2a0dc4aaf740d40307437b2b">mEnableDebug</a></td></tr>
<tr class="separator:a84ad901a2a0dc4aaf740d40307437b2b inherit pro_attribs_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a8e7b5913f3f54d4bb0e6aa8e6071a74a inherit pro_attribs_classtensorNet"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a8e7b5913f3f54d4bb0e6aa8e6071a74a">mAllowGPUFallback</a></td></tr>
<tr class="separator:a8e7b5913f3f54d4bb0e6aa8e6071a74a inherit pro_attribs_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:af7da0313dd945e81649e24b07e0fac0e inherit pro_attribs_classtensorNet"><td class="memItemLeft" align="right" valign="top"><a class="el" href="tensorNet_8h.html#a64c8f3dfeacfa962ff9e23c586aedd1b">Dims3</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#af7da0313dd945e81649e24b07e0fac0e">mInputDims</a></td></tr>
<tr class="separator:af7da0313dd945e81649e24b07e0fac0e inherit pro_attribs_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a3487d6af48f91afcbeea76552d21d1c5 inherit pro_attribs_classtensorNet"><td class="memItemLeft" align="right" valign="top">std::vector&lt; <a class="el" href="structtensorNet_1_1outputLayer.html">outputLayer</a> &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a3487d6af48f91afcbeea76552d21d1c5">mOutputs</a></td></tr>
<tr class="separator:a3487d6af48f91afcbeea76552d21d1c5 inherit pro_attribs_classtensorNet"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table>
<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
<div class="textblock"><p>Image segmentation with FCN-Alexnet or custom models, using TensorRT. </p>
</div><h2 class="groupheader">Member Enumeration Documentation</h2>
<a id="a5579582306d8b98e3a8acf2b73e13ea0"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a5579582306d8b98e3a8acf2b73e13ea0">&#9670;&nbsp;</a></span>FilterMode</h2>

<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">enum <a class="el" href="classsegNet.html#a5579582306d8b98e3a8acf2b73e13ea0">segNet::FilterMode</a></td>
        </tr>
      </table>
</div><div class="memdoc">

<p>Enumeration of mask/overlay filtering modes. </p>
<table class="fieldtable">
<tr><th colspan="2">Enumerator</th></tr><tr><td class="fieldname"><a id="a5579582306d8b98e3a8acf2b73e13ea0abe4ae38cf99cdab6c3b070ee4a83bb47"></a>FILTER_POINT&#160;</td><td class="fielddoc"><p>Nearest point sampling. </p>
</td></tr>
<tr><td class="fieldname"><a id="a5579582306d8b98e3a8acf2b73e13ea0a034092312a95fa984ab6c8e559c3c9e0"></a>FILTER_LINEAR&#160;</td><td class="fielddoc"><p>Bilinear filtering. </p>
</td></tr>
</table>

</div>
</div>
<a id="ab561d3c9e3c733e785aaa790f0f2f660"></a>
<h2 class="memtitle"><span class="permalink"><a href="#ab561d3c9e3c733e785aaa790f0f2f660">&#9670;&nbsp;</a></span>NetworkType</h2>

<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">enum <a class="el" href="classsegNet.html#ab561d3c9e3c733e785aaa790f0f2f660">segNet::NetworkType</a></td>
        </tr>
      </table>
</div><div class="memdoc">

<p>Enumeration of pretrained/built-in network models. </p>
<table class="fieldtable">
<tr><th colspan="2">Enumerator</th></tr><tr><td class="fieldname"><a id="ab561d3c9e3c733e785aaa790f0f2f660adba730fd6f1caee50f8430d96603757a"></a>FCN_ALEXNET_PASCAL_VOC&#160;</td><td class="fielddoc"><p>FCN-Alexnet trained on Pascal VOC dataset. </p>
</td></tr>
<tr><td class="fieldname"><a id="ab561d3c9e3c733e785aaa790f0f2f660a3cb82f1b884ddc9dc8a51381c2cf8420"></a>FCN_ALEXNET_SYNTHIA_CVPR16&#160;</td><td class="fielddoc"><p>FCN-Alexnet trained on SYNTHIA CVPR16 dataset. </p>
<dl class="section note"><dt>Note</dt><dd>To save disk space, this model isn't downloaded by default. Enable it in CMakePreBuild.sh </dd></dl>
</td></tr>
<tr><td class="fieldname"><a id="ab561d3c9e3c733e785aaa790f0f2f660a5808394068d715aeff04991dc34b73a8"></a>FCN_ALEXNET_SYNTHIA_SUMMER_HD&#160;</td><td class="fielddoc"><p>FCN-Alexnet trained on SYNTHIA SEQS summer datasets. </p>
<dl class="section note"><dt>Note</dt><dd>To save disk space, this model isn't downloaded by default. Enable it in CMakePreBuild.sh </dd></dl>
</td></tr>
<tr><td class="fieldname"><a id="ab561d3c9e3c733e785aaa790f0f2f660a245b790d2bc719d2397899bef7472da3"></a>FCN_ALEXNET_SYNTHIA_SUMMER_SD&#160;</td><td class="fielddoc"><p>FCN-Alexnet trained on SYNTHIA SEQS summer datasets. </p>
<dl class="section note"><dt>Note</dt><dd>To save disk space, this model isn't downloaded by default. Enable it in CMakePreBuild.sh </dd></dl>
</td></tr>
<tr><td class="fieldname"><a id="ab561d3c9e3c733e785aaa790f0f2f660a909c376ffd7d5363aea65c200f2e008e"></a>FCN_ALEXNET_CITYSCAPES_HD&#160;</td><td class="fielddoc"><p>FCN-Alexnet trained on Cityscapes dataset with 21 classes. </p>
</td></tr>
<tr><td class="fieldname"><a id="ab561d3c9e3c733e785aaa790f0f2f660a0760a67c5a08aad80d7dc732bc760e31"></a>FCN_ALEXNET_CITYSCAPES_SD&#160;</td><td class="fielddoc"><p>FCN-Alexnet trained on Cityscapes dataset with 21 classes. </p>
<dl class="section note"><dt>Note</dt><dd>To save disk space, this model isn't downloaded by default. Enable it in CMakePreBuild.sh </dd></dl>
</td></tr>
<tr><td class="fieldname"><a id="ab561d3c9e3c733e785aaa790f0f2f660a46829d99af463638dfd4e547b0a2a95d"></a>FCN_ALEXNET_AERIAL_FPV_720p&#160;</td><td class="fielddoc"><p>FCN-Alexnet trained on aerial first-person view of the horizon line for drones, 1280x720 and 21 output classes. </p>
</td></tr>
<tr><td class="fieldname"><a id="ab561d3c9e3c733e785aaa790f0f2f660a95a81cd526c1ada9d225f6142f5f0f41"></a>SEGNET_CUSTOM&#160;</td><td class="fielddoc"></td></tr>
</table>

</div>
</div>
<h2 class="groupheader">Constructor &amp; Destructor Documentation</h2>
<a id="a167f9d7e76b2837485278bf7323b4eac"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a167f9d7e76b2837485278bf7323b4eac">&#9670;&nbsp;</a></span>~segNet()</h2>

<div class="memitem">
<div class="memproto">
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">virtual segNet::~segNet </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td></td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">virtual</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

<p>Destroy. </p>

</div>
</div>
<a id="af2a45b6307104ed74714349becc0495c"></a>
<h2 class="memtitle"><span class="permalink"><a href="#af2a45b6307104ed74714349becc0495c">&#9670;&nbsp;</a></span>segNet()</h2>

<div class="memitem">
<div class="memproto">
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">segNet::segNet </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td></td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">protected</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

</div>
</div>
<h2 class="groupheader">Member Function Documentation</h2>
<a id="a3b98b9827d5c07e84ed6711414b96554"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a3b98b9827d5c07e84ed6711414b96554">&#9670;&nbsp;</a></span>classify()</h2>

<div class="memitem">
<div class="memproto">
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">bool segNet::classify </td>
          <td>(</td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>ignore_class</em></td><td>)</td>
          <td></td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">protected</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

</div>
</div>
<a id="a0679f72dbced85d919d01af841c67db9"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a0679f72dbced85d919d01af841c67db9">&#9670;&nbsp;</a></span>Create() <span class="overload">[1/3]</span></h2>

<div class="memitem">
<div class="memproto">
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">static <a class="el" href="classsegNet.html">segNet</a>* segNet::Create </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="classsegNet.html#ab561d3c9e3c733e785aaa790f0f2f660">NetworkType</a>&#160;</td>
          <td class="paramname"><em>networkType</em> = <code><a class="el" href="classsegNet.html#ab561d3c9e3c733e785aaa790f0f2f660a0760a67c5a08aad80d7dc732bc760e31">FCN_ALEXNET_CITYSCAPES_SD</a></code>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>maxBatchSize</em> = <code><a class="el" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a></code>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a>&#160;</td>
          <td class="paramname"><em>precision</em> = <code><a class="el" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a></code>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a>&#160;</td>
          <td class="paramname"><em>device</em> = <code><a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a></code>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">bool&#160;</td>
          <td class="paramname"><em>allowGPUFallback</em> = <code>true</code>&#160;</td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">static</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

<p>Load a new network instance. </p>

</div>
</div>
<a id="aee471c7f0b830babb826648db2692edb"></a>
<h2 class="memtitle"><span class="permalink"><a href="#aee471c7f0b830babb826648db2692edb">&#9670;&nbsp;</a></span>Create() <span class="overload">[2/3]</span></h2>

<div class="memitem">
<div class="memproto">
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">static <a class="el" href="classsegNet.html">segNet</a>* segNet::Create </td>
          <td>(</td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>prototxt_path</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>model_path</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>class_labels</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>class_colors</em> = <code>NULL</code>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>input</em> = <code><a class="el" href="group__segNet.html#ga33b5fd20f8ed468725c55eb0bcc5af71">SEGNET_DEFAULT_INPUT</a></code>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>output</em> = <code><a class="el" href="group__segNet.html#ga05c359c7dcd0c1e855543a3a9a18c422">SEGNET_DEFAULT_OUTPUT</a></code>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>maxBatchSize</em> = <code><a class="el" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a></code>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a>&#160;</td>
          <td class="paramname"><em>precision</em> = <code><a class="el" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a></code>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a>&#160;</td>
          <td class="paramname"><em>device</em> = <code><a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a></code>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">bool&#160;</td>
          <td class="paramname"><em>allowGPUFallback</em> = <code>true</code>&#160;</td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">static</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

<p>Load a new network instance. </p>
<dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramname">prototxt_path</td><td>File path to the deployable network prototxt </td></tr>
    <tr><td class="paramname">model_path</td><td>File path to the caffemodel </td></tr>
    <tr><td class="paramname">class_labels</td><td>File path to list of class name labels </td></tr>
    <tr><td class="paramname">class_colors</td><td>File path to list of class colors </td></tr>
    <tr><td class="paramname">input</td><td>Name of the input layer blob. </td></tr>
  </table>
  </dd>
</dl>
<dl class="section see"><dt>See also</dt><dd><a class="el" href="group__segNet.html#ga33b5fd20f8ed468725c55eb0bcc5af71" title="Name of default input blob for segmentation model. ">SEGNET_DEFAULT_INPUT</a> </dd></dl>
<dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramname">output</td><td>Name of the output layer blob. </td></tr>
  </table>
  </dd>
</dl>
<dl class="section see"><dt>See also</dt><dd><a class="el" href="group__segNet.html#ga05c359c7dcd0c1e855543a3a9a18c422" title="Name of default output blob for segmentation model. ">SEGNET_DEFAULT_OUTPUT</a> </dd></dl>
<dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramname">maxBatchSize</td><td>The maximum batch size that the network will support and be optimized for. </td></tr>
  </table>
  </dd>
</dl>

</div>
</div>
<a id="aa4186752e1402963fdde8e2d6f2613d7"></a>
<h2 class="memtitle"><span class="permalink"><a href="#aa4186752e1402963fdde8e2d6f2613d7">&#9670;&nbsp;</a></span>Create() <span class="overload">[3/3]</span></h2>

<div class="memitem">
<div class="memproto">
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">static <a class="el" href="classsegNet.html">segNet</a>* segNet::Create </td>
          <td>(</td>
          <td class="paramtype">int&#160;</td>
          <td class="paramname"><em>argc</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">char **&#160;</td>
          <td class="paramname"><em>argv</em>&#160;</td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">static</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

<p>Load a new network instance by parsing the command line. </p>

</div>
</div>
<a id="a299e7f53cde4e3e25cd00829dc181a10"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a299e7f53cde4e3e25cd00829dc181a10">&#9670;&nbsp;</a></span>FilterModeFromStr()</h2>

<div class="memitem">
<div class="memproto">
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">static <a class="el" href="classsegNet.html#a5579582306d8b98e3a8acf2b73e13ea0">FilterMode</a> segNet::FilterModeFromStr </td>
          <td>(</td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>str</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="classsegNet.html#a5579582306d8b98e3a8acf2b73e13ea0">FilterMode</a>&#160;</td>
          <td class="paramname"><em>default_value</em> = <code><a class="el" href="classsegNet.html#a5579582306d8b98e3a8acf2b73e13ea0a034092312a95fa984ab6c8e559c3c9e0">FILTER_LINEAR</a></code>&#160;</td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">static</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

<p>Parse a string from one of the FilterMode values. </p>
<p>Valid strings are "point", and "linear" </p><dl class="section return"><dt>Returns</dt><dd>one of the <a class="el" href="classsegNet.html#a5579582306d8b98e3a8acf2b73e13ea0" title="Enumeration of mask/overlay filtering modes. ">segNet::FilterMode</a> enums, or default <a class="el" href="classsegNet.html#a5579582306d8b98e3a8acf2b73e13ea0a034092312a95fa984ab6c8e559c3c9e0" title="Bilinear filtering. ">segNet::FILTER_LINEAR</a> on an error. </dd></dl>

</div>
</div>
<a id="a04bb46f8a71a45044d324a5e140f0777"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a04bb46f8a71a45044d324a5e140f0777">&#9670;&nbsp;</a></span>FindClassID()</h2>

<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">int segNet::FindClassID </td>
          <td>(</td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>label_name</em></td><td>)</td>
          <td></td>
        </tr>
      </table>
</div><div class="memdoc">

<p>Find the ID of a particular class (by label name). </p>

</div>
</div>
<a id="a07e9a40b797f22ed0f0e83479be57d17"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a07e9a40b797f22ed0f0e83479be57d17">&#9670;&nbsp;</a></span>GetClassColor()</h2>

<div class="memitem">
<div class="memproto">
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">float* segNet::GetClassColor </td>
          <td>(</td>
          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>id</em></td><td>)</td>
          <td> const</td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">inline</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

<p>Retrieve the class synset category of a particular class. </p>

</div>
</div>
<a id="a895252269f201c23e8887d2774ec5ac4"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a895252269f201c23e8887d2774ec5ac4">&#9670;&nbsp;</a></span>GetClassLabel()</h2>

<div class="memitem">
<div class="memproto">
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">const char* segNet::GetClassLabel </td>
          <td>(</td>
          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>id</em></td><td>)</td>
          <td> const</td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">inline</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

<p>Retrieve the description of a particular class. </p>

</div>
</div>
<a id="a973c337a2c3d7371c6b7cebd3aa2ade0"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a973c337a2c3d7371c6b7cebd3aa2ade0">&#9670;&nbsp;</a></span>GetClassPath()</h2>

<div class="memitem">
<div class="memproto">
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">const char* segNet::GetClassPath </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td> const</td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">inline</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

<p>Retrieve the path to the file containing the class label descriptions. </p>

</div>
</div>
<a id="a95980d825a9939d0f48bfb2ef51ebb79"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a95980d825a9939d0f48bfb2ef51ebb79">&#9670;&nbsp;</a></span>GetGridHeight()</h2>

<div class="memitem">
<div class="memproto">
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">uint32_t segNet::GetGridHeight </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td> const</td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">inline</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

<p>Retrieve the number of rows in the classification grid. </p>
<p>This indicates the resolution of the raw segmentation output. </p>

</div>
</div>
<a id="a96b6fe6b05534c0792f8cc9353723219"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a96b6fe6b05534c0792f8cc9353723219">&#9670;&nbsp;</a></span>GetGridWidth()</h2>

<div class="memitem">
<div class="memproto">
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">uint32_t segNet::GetGridWidth </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td> const</td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">inline</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

<p>Retrieve the number of columns in the classification grid. </p>
<p>This indicates the resolution of the raw segmentation output. </p>

</div>
</div>
<a id="a94b243146a1391e82612cb70641c4bac"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a94b243146a1391e82612cb70641c4bac">&#9670;&nbsp;</a></span>GetNetworkName()</h2>

<div class="memitem">
<div class="memproto">
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">const char* segNet::GetNetworkName </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td> const</td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">inline</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

<p>Retrieve a string describing the network name. </p>

</div>
</div>
<a id="a7779565e2e627209d6fc6e7562047431"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a7779565e2e627209d6fc6e7562047431">&#9670;&nbsp;</a></span>GetNetworkType()</h2>

<div class="memitem">
<div class="memproto">
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname"><a class="el" href="classsegNet.html#ab561d3c9e3c733e785aaa790f0f2f660">NetworkType</a> segNet::GetNetworkType </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td> const</td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">inline</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

<p>Retrieve the network type (alexnet or googlenet) </p>

</div>
</div>
<a id="a31e8118b2a38e330b6e087cf6c98396e"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a31e8118b2a38e330b6e087cf6c98396e">&#9670;&nbsp;</a></span>GetNumClasses()</h2>

<div class="memitem">
<div class="memproto">
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">uint32_t segNet::GetNumClasses </td>
          <td>(</td>
          <td class="paramname"></td><td>)</td>
          <td> const</td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">inline</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

<p>Retrieve the number of object classes supported in the detector. </p>

</div>
</div>
<a id="a218a2c71cb4d59476070385c7370f789"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a218a2c71cb4d59476070385c7370f789">&#9670;&nbsp;</a></span>loadClassColors()</h2>

<div class="memitem">
<div class="memproto">
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">bool segNet::loadClassColors </td>
          <td>(</td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>filename</em></td><td>)</td>
          <td></td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">protected</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

</div>
</div>
<a id="a31d2bd6ddf05ce178a8e6c5b88247075"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a31d2bd6ddf05ce178a8e6c5b88247075">&#9670;&nbsp;</a></span>loadClassLabels()</h2>

<div class="memitem">
<div class="memproto">
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">bool segNet::loadClassLabels </td>
          <td>(</td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>filename</em></td><td>)</td>
          <td></td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">protected</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

</div>
</div>
<a id="a1efb45b81c82dd6f74c641ab39a41387"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a1efb45b81c82dd6f74c641ab39a41387">&#9670;&nbsp;</a></span>Mask() <span class="overload">[1/2]</span></h2>

<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">bool segNet::Mask </td>
          <td>(</td>
          <td class="paramtype">uint8_t *&#160;</td>
          <td class="paramname"><em>output</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>width</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>height</em>&#160;</td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table>
</div><div class="memdoc">

<p>Produce a grayscale binary segmentation mask, where the pixel values correspond to the class ID of the corresponding class type. </p>

</div>
</div>
<a id="a656d709bbfb00fb0b9b4d55296aae463"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a656d709bbfb00fb0b9b4d55296aae463">&#9670;&nbsp;</a></span>Mask() <span class="overload">[2/2]</span></h2>

<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">bool segNet::Mask </td>
          <td>(</td>
          <td class="paramtype">float *&#160;</td>
          <td class="paramname"><em>output</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>width</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>height</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="classsegNet.html#a5579582306d8b98e3a8acf2b73e13ea0">FilterMode</a>&#160;</td>
          <td class="paramname"><em>filter</em> = <code><a class="el" href="classsegNet.html#a5579582306d8b98e3a8acf2b73e13ea0a034092312a95fa984ab6c8e559c3c9e0">FILTER_LINEAR</a></code>&#160;</td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table>
</div><div class="memdoc">

<p>Produce a colorized RGBA segmentation mask. </p>

</div>
</div>
<a id="a586492c234d2dc924458e99d6026dbb4"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a586492c234d2dc924458e99d6026dbb4">&#9670;&nbsp;</a></span>NetworkTypeFromStr()</h2>

<div class="memitem">
<div class="memproto">
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">static <a class="el" href="classsegNet.html#ab561d3c9e3c733e785aaa790f0f2f660">NetworkType</a> segNet::NetworkTypeFromStr </td>
          <td>(</td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>model_name</em></td><td>)</td>
          <td></td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">static</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

<p>Parse a string from one of the built-in pretrained models. </p>
<p>Valid names are "cityscapes-hd", "cityscapes-sd", "pascal-voc", ect. </p><dl class="section return"><dt>Returns</dt><dd>one of the <a class="el" href="classsegNet.html#ab561d3c9e3c733e785aaa790f0f2f660" title="Enumeration of pretrained/built-in network models. ">segNet::NetworkType</a> enums, or segNet::CUSTOM on invalid string. </dd></dl>

</div>
</div>
<a id="a3a670c08ad8b13db6ee092c59efe88b8"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a3a670c08ad8b13db6ee092c59efe88b8">&#9670;&nbsp;</a></span>Overlay()</h2>

<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">bool segNet::Overlay </td>
          <td>(</td>
          <td class="paramtype">float *&#160;</td>
          <td class="paramname"><em>output</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>width</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>height</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="classsegNet.html#a5579582306d8b98e3a8acf2b73e13ea0">FilterMode</a>&#160;</td>
          <td class="paramname"><em>filter</em> = <code><a class="el" href="classsegNet.html#a5579582306d8b98e3a8acf2b73e13ea0a034092312a95fa984ab6c8e559c3c9e0">FILTER_LINEAR</a></code>&#160;</td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table>
</div><div class="memdoc">

<p>Produce the segmentation overlay alpha blended on top of the original image. </p>
<dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramname">input</td><td>float4 input image in CUDA device memory, RGBA colorspace with values 0-255. </td></tr>
    <tr><td class="paramname">output</td><td>float4 output image in CUDA device memory, RGBA colorspace with values 0-255. </td></tr>
    <tr><td class="paramname">width</td><td>width of the input image in pixels. </td></tr>
    <tr><td class="paramname">height</td><td>height of the input image in pixels. </td></tr>
    <tr><td class="paramname">ignore_class</td><td>label name of class to ignore in the classification (or NULL to process all). </td></tr>
    <tr><td class="paramname">type</td><td>overlay visualization options </td></tr>
  </table>
  </dd>
</dl>
<dl class="section return"><dt>Returns</dt><dd>true on success, false on error. </dd></dl>

</div>
</div>
<a id="a1365e866302f49f6fe7f9fe95cbe6a72"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a1365e866302f49f6fe7f9fe95cbe6a72">&#9670;&nbsp;</a></span>overlayLinear()</h2>

<div class="memitem">
<div class="memproto">
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">bool segNet::overlayLinear </td>
          <td>(</td>
          <td class="paramtype">float *&#160;</td>
          <td class="paramname"><em>input</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>in_width</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>in_height</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">float *&#160;</td>
          <td class="paramname"><em>output</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>out_width</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>out_height</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">bool&#160;</td>
          <td class="paramname"><em>mask_only</em>&#160;</td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">protected</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

</div>
</div>
<a id="a3691c49b64e20993bb2440129a7cd81e"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a3691c49b64e20993bb2440129a7cd81e">&#9670;&nbsp;</a></span>overlayPoint()</h2>

<div class="memitem">
<div class="memproto">
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">bool segNet::overlayPoint </td>
          <td>(</td>
          <td class="paramtype">float *&#160;</td>
          <td class="paramname"><em>input</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>in_width</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>in_height</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">float *&#160;</td>
          <td class="paramname"><em>output</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>out_width</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>out_height</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">bool&#160;</td>
          <td class="paramname"><em>mask_only</em>&#160;</td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">protected</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

</div>
</div>
<a id="a2fe1beec3215b5d7744420b57ba397c4"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a2fe1beec3215b5d7744420b57ba397c4">&#9670;&nbsp;</a></span>Process()</h2>

<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">bool segNet::Process </td>
          <td>(</td>
          <td class="paramtype">float *&#160;</td>
          <td class="paramname"><em>input</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>width</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>height</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>ignore_class</em> = <code>&quot;void&quot;</code>&#160;</td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table>
</div><div class="memdoc">

<p>Perform the initial inferencing processing portion of the segmentation. </p>
<p>The results can then be visualized using the <a class="el" href="classsegNet.html#a3a670c08ad8b13db6ee092c59efe88b8" title="Produce the segmentation overlay alpha blended on top of the original image. ">Overlay()</a> and <a class="el" href="classsegNet.html#a1efb45b81c82dd6f74c641ab39a41387" title="Produce a grayscale binary segmentation mask, where the pixel values correspond to the class ID of th...">Mask()</a> functions. </p><dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramname">input</td><td>float4 input image in CUDA device memory, RGBA colorspace with values 0-255. </td></tr>
    <tr><td class="paramname">width</td><td>width of the input image in pixels. </td></tr>
    <tr><td class="paramname">height</td><td>height of the input image in pixels. </td></tr>
    <tr><td class="paramname">ignore_class</td><td>label name of class to ignore in the classification (or NULL to process all). </td></tr>
  </table>
  </dd>
</dl>

</div>
</div>
<a id="a2a9108ad71f4d5f1995ac58282a10b88"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a2a9108ad71f4d5f1995ac58282a10b88">&#9670;&nbsp;</a></span>SetClassColor()</h2>

<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">void segNet::SetClassColor </td>
          <td>(</td>
          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>classIndex</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">float&#160;</td>
          <td class="paramname"><em>r</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">float&#160;</td>
          <td class="paramname"><em>g</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">float&#160;</td>
          <td class="paramname"><em>b</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">float&#160;</td>
          <td class="paramname"><em>a</em> = <code>255.0f</code>&#160;</td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table>
</div><div class="memdoc">

<p>Set the visualization color of a particular class of object. </p>

</div>
</div>
<a id="a12d132d630f471c64ad943cbbffb2851"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a12d132d630f471c64ad943cbbffb2851">&#9670;&nbsp;</a></span>SetGlobalAlpha()</h2>

<div class="memitem">
<div class="memproto">
      <table class="memname">
        <tr>
          <td class="memname">void segNet::SetGlobalAlpha </td>
          <td>(</td>
          <td class="paramtype">float&#160;</td>
          <td class="paramname"><em>alpha</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">bool&#160;</td>
          <td class="paramname"><em>explicit_exempt</em> = <code>true</code>&#160;</td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
      </table>
</div><div class="memdoc">

<p>Set a global alpha value for all classes (between 0-255), (optionally except for those that have been explicitly set). </p>

</div>
</div>
<h2 class="groupheader">Member Data Documentation</h2>
<a id="adbf7de9cddd287f99a1ef7edf531325c"></a>
<h2 class="memtitle"><span class="permalink"><a href="#adbf7de9cddd287f99a1ef7edf531325c">&#9670;&nbsp;</a></span>mClassColors</h2>

<div class="memitem">
<div class="memproto">
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">float* segNet::mClassColors[2]</td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">protected</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

<p>array of overlay colors in shared CPU/GPU memory </p>

</div>
</div>
<a id="a5763fca156e99d9fe07dcbf626489b0e"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a5763fca156e99d9fe07dcbf626489b0e">&#9670;&nbsp;</a></span>mClassLabels</h2>

<div class="memitem">
<div class="memproto">
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">std::vector&lt;std::string&gt; segNet::mClassLabels</td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">protected</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

</div>
</div>
<a id="ac1f23154131a719769edf4811f8762ef"></a>
<h2 class="memtitle"><span class="permalink"><a href="#ac1f23154131a719769edf4811f8762ef">&#9670;&nbsp;</a></span>mClassMap</h2>

<div class="memitem">
<div class="memproto">
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">uint8_t* segNet::mClassMap[2]</td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">protected</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

<p>runtime buffer for the argmax-classified class index of each tile </p>

</div>
</div>
<a id="af9a9bd73dc17940aa87aacba2001b09b"></a>
<h2 class="memtitle"><span class="permalink"><a href="#af9a9bd73dc17940aa87aacba2001b09b">&#9670;&nbsp;</a></span>mClassPath</h2>

<div class="memitem">
<div class="memproto">
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">std::string segNet::mClassPath</td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">protected</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

</div>
</div>
<a id="a4341b8ae226236eef40867bab4c7f251"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a4341b8ae226236eef40867bab4c7f251">&#9670;&nbsp;</a></span>mLastInputHeight</h2>

<div class="memitem">
<div class="memproto">
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">uint32_t segNet::mLastInputHeight</td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">protected</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

<p>height in pixels of last input image to be processed </p>

</div>
</div>
<a id="ad7970fe3c387258828d628bd5f08e57a"></a>
<h2 class="memtitle"><span class="permalink"><a href="#ad7970fe3c387258828d628bd5f08e57a">&#9670;&nbsp;</a></span>mLastInputImg</h2>

<div class="memitem">
<div class="memproto">
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">float* segNet::mLastInputImg</td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">protected</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

<p>last input image to be processed, stored for overlay </p>

</div>
</div>
<a id="ad984bfe4460621a78440bfb4768f4e8e"></a>
<h2 class="memtitle"><span class="permalink"><a href="#ad984bfe4460621a78440bfb4768f4e8e">&#9670;&nbsp;</a></span>mLastInputWidth</h2>

<div class="memitem">
<div class="memproto">
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname">uint32_t segNet::mLastInputWidth</td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">protected</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

<p>width in pixels of last input image to be processed </p>

</div>
</div>
<a id="a9719a3525dd0ee4bcc0e954187dc7323"></a>
<h2 class="memtitle"><span class="permalink"><a href="#a9719a3525dd0ee4bcc0e954187dc7323">&#9670;&nbsp;</a></span>mNetworkType</h2>

<div class="memitem">
<div class="memproto">
<table class="mlabels">
  <tr>
  <td class="mlabels-left">
      <table class="memname">
        <tr>
          <td class="memname"><a class="el" href="classsegNet.html#ab561d3c9e3c733e785aaa790f0f2f660">NetworkType</a> segNet::mNetworkType</td>
        </tr>
      </table>
  </td>
  <td class="mlabels-right">
<span class="mlabels"><span class="mlabel">protected</span></span>  </td>
  </tr>
</table>
</div><div class="memdoc">

<p>Pretrained built-in model type enumeration. </p>

</div>
</div>
<hr/>The documentation for this class was generated from the following file:<ul>
<li>jetson-inference/<a class="el" href="segNet_8h_source.html">segNet.h</a></li>
</ul>
</div><!-- contents -->
</div><!-- doc-content -->
<!-- start footer part -->
<div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
  <ul>
    <li class="navelem"><a class="el" href="classsegNet.html">segNet</a></li>
    <li class="footer">Generated on Fri Jun 21 2019 16:23:15 for Jetson Inference by
    <a href="http://www.doxygen.org/index.html">
    <img class="footer" src="doxygen.png" alt="doxygen"/></a> 1.8.13 </li>
  </ul>
</div>
</body>
</html>
